Yeswanth Narra

If you’re building machine learning solutions with sensitive data, you face a persistent challenge: preventing data exfiltration while enabling data scientists to work productively. iBusiness, an AI-driven fintech organization, needed its data scientists to work with sensitive data to fine-tune and improve machine learning models.

AWS Storage Blog Modern enterprises routinely manage billions of objects across their cloud storage environments, needing efficient bulk operations for disaster recovery, compliance management, data transfer, and cost optimization. Performing these operations manually or through custom scripts becomes impractical at scale, often creating operational bottlenecks when time-sensitive actions are necessary.